Triple
T27968264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 畲族 |
E704784
|
entity |
| Predicate | 主要分布地区 |
P55272
|
FINISHED |
| Object | 中国南方 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 中国南方 | Statement: [畲族, 主要分布地区, 中国南方]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 主要分布地区 Context triple: [畲族, 主要分布地区, 中国南方]
-
A.
geographicDistribution
Indicates the spatial range or area over which something occurs, exists, or is found.
-
B.
ownedAndDistributedInManyRegionsBy
Indicates that something is possessed and actively supplied or made available across multiple geographic areas by a particular entity.
-
C.
countryOrRegionOfPrevalence
chosen
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
D.
geographicRangeType
Indicates the kind of geographic range or distribution pattern that characterizes where an entity occurs or is found.
-
E.
hasGlobalDistribution
Indicates that the related entity occurs, operates, or is present across most or all regions of the world rather than being confined to a specific locality or region.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63b3337748190ae03ce1742a31d22 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:36 p.m.